Understanding the business challenge
As MEDITECH (Client in the US) institutions adopted the Patient Chart, we focused on understanding how clinicians interact with patient data in real-world scenarios to improve usability and support scalable adoption.
Objective
Identify real usage patterns across clinicians
Reduce friction in navigating patient data
Improve clarity and speed in critical workflows
Enable scalable adoption across clinics, labs, and hospitals
Insight & Problem
Through UX sessions, interviews, and usability testing with MEDITECH providers, we identified a critical gap in how clinicians interact with patient data.
Providers valued having access to comprehensive patient data, but in high-pressure environments like the emergency room, the experience broke down.
Instead of navigating across multiple modules—each with its own filters and structure—they needed a single, integrated view.
A key insight emerged:
Clinicians don’t explore data broadly in critical moments—they focus on a specific condition.
For example, during a cardiac event, they need immediate access to all relevant information—labs, medications, encounters—connected to that diagnosis, without switching contexts.
Approach (Design Thinking)
1. UX Sessions & Stakeholder Alignment
Collaborated with clinicians, PMs, and business stakeholders to observe real workflows and define key problems.
2. Journey Mapping & Workflow Analysis
Mapped how providers access, interpret, and switch between patient data sources.
3. Research Synthesis
Identified core friction points:
High cognitive load
Fragmented data views
Lack of clear hierarchy and context
4. Rapid Prototyping & Testing
Explored multiple interaction models and validated them through iterative feedback sessions.
Designing the experience
Key design principles:
Clarity over density → Simplify complex datasets
Contextual navigation → Group related information
Progressive disclosure → Show detail on demand
System thinking → Align with design system for scalability
Solution
HumanGraph introduces a connected, visual representation of patient data:
Timeline-based structure to organize events
Contextual filters for quick exploration
Unified view across multiple data sources
On-demand details for deeper insights
First iteration - integrated view
Second iteration with diagnosis filter implemented
Outcome
Clinicians can now enter the experience with a specific focus and instantly access all relevant information in one place—enabling faster understanding and more confident decision-making in critical moments.
Impact
Scaled adoption from 3 to 250+ clinics in one year
Faster clinical insights through improved data clarity
Reduced cognitive load and navigation friction
Enabled scalable rollout across MEDITECH institutions
